Evolution of high‐latitude snow mass derived from the GRACE gravimetry mission (2002–2004)
Bibliographic record
Abstract
Since March 2002, the GRACE mission provides monthly global maps of geoid time‐variations. These new data carry information on the continental water storage, including snow mass variations, with a ground resolution of ∼600–700 km. We have computed monthly snow mass solutions from the inversion of the 22 GRACE geoids (04/2002–05/2004). The inverse approach developed here allows to separate the soil waters from snow signal. These snow mass solutions are further compared to predictions from three global land surface models and snow depths derived from satellite microwave data. We find that the GRACE solutions correlate well with the high‐latitude zones of strong accumulation of snow. Regional means computed for four large boreal basins (Yenisey, Ob, Mac Kenzie and Yukon) show a good agreement at seasonal scale between the snow mass solutions and model predictions (global rms ∼30–40 mm of equivalent‐water height and ∼10–20 mm regionally).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".